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A paper field classification method suitable for a literature network

A classification method and network technology, applied in the field of information retrieval to achieve the effect of reducing dimensionality

Active Publication Date: 2019-05-28
FUZHOU UNIV
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Problems solved by technology

[0003] In addition, the continuous expansion of data scale and the continuous growth of data dimensions in the literature network have brought many problems to data analysis and processing.

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  • A paper field classification method suitable for a literature network
  • A paper field classification method suitable for a literature network
  • A paper field classification method suitable for a literature network

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Embodiment Construction

[0039] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0040] A kind of paper field classification method suitable for literature network proposed by the present invention, such as figure 1 shown, including the following steps:

[0041] Step S1, given a literature network G=(V, E), find out the metastructure S of the literature network G according to the network model, wherein, V is a set of nodes, and E is a set of relationships between nodes;

[0042] Step S2. For all paper nodes in the literature network G, based on the meta-structure S, designate a node as the source object o s , a node as the target object o t , from the source node o s Starting from each level of the meta-structure S, according to the link expansion in the network document G, the sub-graph g of each layer layer under the restriction of the meta-structure S is generated, and o s with o tThe correlation degree in the...

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Abstract

The invention relates to a paper field classification method suitable for a literature network, which comprises the following steps of selecting the literature network, and firstly calculating the correlation degree among paper nodes based on a meta-structure; defining an objective function to minimize the difference between the correlation degree based on a meta-structure between the paper nodesand the similarity of the paper nodes in a low-dimensional vector space, and mapping the paper nodes in the literature network to a low-dimensional representation space; and calculating the similaritybetween the paper nodes in a low-dimensional space, and carrying out K-means clustering to obtain a field classification result of the paper. According to the method provided by the invention, the importance characteristic of a meta-structure in the heterogeneous information network is utilized, so that the low-dimensional vector representation of the node can fuse rich heterogeneous informationin the network while containing the topological structure information of the node network, and the field to which the paper belongs can be better classified.

Description

technical field [0001] The invention relates to the field of information retrieval, in particular to a paper field classification method suitable for literature networks. Background technique [0002] With the popularity of literature networks in various disciplines, various needs of users have been born when using them. For example, recommending a suitable conference or journal for a paper; finding other latest papers that may be of interest to scholars, and so on. When scholars need to understand a new research field, they can start by browsing papers in this type of field. Therefore, it becomes important to classify the domains of papers in the literature network. In general, the more similar two paper nodes within a network are, the more likely they are of the same field. As a typical heterogeneous information network, the literature network has a wealth of behavioral and other semantic information between its nodes, such as the author published a paper, the paper was...

Claims

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Application Information

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IPC IPC(8): G06F16/35
Inventor 王秀余春艳陈璐
Owner FUZHOU UNIV
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